Group 29 Presentation

s224965: Mille Grinder
s224989: Amalie Frøsig
s225059: Niels Elfenbein
s250441: Tomás Raskovsky
s251977: Frida De los Rios

Introduction

  • CD molecules are membrane proteins with diverse functions and distributions across immune cell types.

  • Their expression patterns help distinguish cell lineages and reveal functional relationships

Aim:

  • How do the expression of CD markers on lymphocyte subsets change during maturation?

  • How are fluorescence intensity, variability, and positivity (MedQb, CVQb, PEpos) related across CD markers in lymphocyte subsets?

Data from:

  • Frontiers in Immunology, “B Cell Biology,” vol. 10, Oct. 23, 2019. doi: 10.3389/fimmu.2019.02434

  • Can be downloaded from their shiny app: http://bioinformin.cesnet.cz/CDmaps/

DOI: 10.5772/intechopen.81568

Materials and Methods

  • The data set contains:

    • 28340 observations of 8 variables

    • 114 unique CDs and 38 unique cell types

  • Selected variables:

    • CVQB, MedQb and PEpos

Sample of data_aug:

# A tibble: 5 × 8
  tissue CD          lineage     cell_type hierarchy   CVQb   MedQb    PEpos
  <chr>  <chr>       <chr>       <chr>         <dbl>  <dbl>   <dbl>    <dbl>
1 tonsil CD62P       B cells     CC                3  101.    600.    0.457 
2 thymus CD11a       Thymocytes  DN34p             4   22.3 10414.  100     
3 blood  CD68        CD8 T cells TCD8RAdim         4 1294.     65.3   0.0732
4 blood  CD4_MEM-241 B cells     BnatEff           3  133.    294.    1     
5 thymus CD81        Thymocytes  CD4SP1ap          4  120.   9507.   98.9

PCA of MedQb and PEpos

  • MedQb:
    • Three distinct clusters
    • Thymocytes cluster with T-cells from blood
    • B-cells form a tonsil cluster and a blood cluster
  • PEpos:
    • Four distinct clusters
    • Thymocytes and blood T cells are seperated in two clusters
    • B-cells from blood and tonsil seperate in PC2, but very similar in PC1

Overview of CD markers

  • Wide variations in CD marker distribution

  • Tissue-related clusters are common

  • Some markers are universally expressed (e.g. CD45), with others are lineage-specific

How does MedQb correlate with CVQb and PEpos?

CVQb:

  • Blue lines show a negative correlation → higher CVQb = lower MedQb

  • Tonsil B cells: line is flat → almost no relationship

PEpos:

  • Pink lines show a positive correlation → higher PEpos = higher MedQb

How does CD expression change during maturation?

  • For each tissue and lineage, a linear model was applied with the naive cell as the reference

  • B cells had the most significant markers, showing stronger activation changes

How does CD expression change during maturation?

  • Tonsil B cells are more activated (CD69, CD80), while blood B cells mature gradually (CD11a, CD80)

  • CD4 and CD8 T cells follow a similar pattern. Develop in the thymus and become more specialized and mature in the blood. 

How do CD markers differ between CD4 and CD8 T cells?

  • CD4 and CD8 T cells go through parallel stages

  • SP1am and naive subsets have the lowest number of significant CDs → CD4 and CD8 more similar in CD expression in these stages

How do CD markers differ between CD4 and CD8 T cells?

  • As expected CD4 and CD8 are significant different for all pairs

  • CD59 is significant for all stages except TEMRA with a higher log(MedQb) for CD4 T cells

Discussion

Why did we choose the linear model to assess significant difference for CDs?

  • Simple method to compare each subset to the naive cell

  • An ANOVA could for example also have been used for pairwise comparison

Problems with missing values in the wide-format data set for PCA

  • Number of experiments for each CD differed → summarized the experiments by the mean

  • Not every CD marker was measured across all cell types → replaced the missing value with the median for that specific CD

  • Limits the variation in the data set, but necessary to avoid dropping observations